正学AL:一个闪亮的应用程序,用于对非人类临床前高维基因表达数据的质量意识的人性化
Rishika Chowdary1, Robert K Suter1, Matthew D'Antuono1
1Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC 20007, United States.
Bioinformatics (Oxford, England)
|May 20, 2025
概括
通过将非人类的转录基因数据转换为人类的ortolog,使药物发现应用成为可能,OrthologAL促进了临床前研究. 该工具简化了在转化研究中使用来自不同物种的有价值的基因表达数据集.
科学领域:
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
- 翻译医学是一种翻译医学.
背景情况:
- 单细胞和空间转录组学提供了深刻的生物学见解,但难以跨物种应用.
- 药物转录学利用基因表达来发现药物,但临床前模型需要跨物种数据转换.
- 现有的资源往往缺乏对非人类转录组的支持,阻碍了翻译研究.
研究的目的:
- 介绍OrthologAL,这是一个用于将非人类的转录数据转换为人类的ortolog的工具.
- 为了使人类药物转录数据库能够应用于临床前研究模型.
- 为了简化在药物发现中使用来自不同物种的基因表达数据.
主要方法:
- OrthologAL 与 BioMart 和 Ensembl 进行接口,以执行基因组的 Ortholog 转换.
- 该工具接受含有单细胞,单核或空间转录组数据的Seurat对象.
- 它输出了转换为人类正义词的Seurat对象,保留了数据的维度.
主要成果:
- 奥尔托洛格AL成功地转换了来自各种临床前模型 (骨髓母细胞瘤外移植,脊髓损伤模型) 的转录组数据.
- 转换过程有效地识别了人类的正义符号,同时保持了原始数据的维度架构.
- 在将临床前数据应用于人类衍生的小分子预测中证明了实用性.
结论:
- OrthologAL提供了一个用户友好的解决方案,用于跨物种的转录数据转换.
- 它显著提高了临床前基因表达数据的实用性,用于以人类为中心的药物发现.
- R包和Shiny GUI促进了研究环境中的广泛采用.
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